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#ifndef ERROR_EST
#define ERROR_EST
#include <core/fitter.hpp>
#include <iostream>
#include <vector>
#include <string>
namespace opt_utilities
{
template <typename Ty,typename Tx,typename Tp,typename Ts,typename Tstr>
void estimate_error(fitter<Ty,Tx,Tp,Ts>& fit,const Tstr& pname,typename element_type_trait<Tp>::element_type& lower,typename element_type_trait<Tp>::element_type& upper,const Ts& dchi)
{
typedef typename element_type_trait<Tp>::element_type Tpe;
std::vector<Tstr> pnames;
std::vector<Tpe> pvalues;
for(int i=0;i<fit.get_num_params();++i)
{
pnames.push_back(fit.get_param_info(i).get_name());
pvalues.push_back(fit.get_param_info(i).get_value());
}
fit.fit();
if(fit.report_param_status(pname)=="frozen")
{
return;
}
try
{
freeze_param<Ty,Tx,Tp,Tstr>* pfp=dynamic_cast<freeze_param<Ty,Tx,Tp,Tstr>*>(&fit.get_param_modifier());
if(pfp==0)
{
assert(0);
}
*pfp+=freeze_param<Ty,Tx,Tp,Tstr>(pname);
}
catch(const param_modifier_undefined&)
{
fit.set_param_modifier(freeze_param<Ty,Tx,Tp,Tstr>(pname));
}
Tpe current_value=
fit.get_param_value(pname);
Tp current_params(fit.get_model().get_all_params());
Ts current_chi=fit.get_statistic_value();
Tpe upper1=current_value;
Tpe step=upper-current_value;
while(1)
{
fit.set_param_value(pname,upper);
fit.fit();
Ts chi=fit.get_statistic_value();
cerr<<upper<<"\t"<<chi<<std::endl;
if(chi>current_chi+dchi)
{
break;
}
upper+=step;
}
Ts target_chi=current_chi+dchi;
while(upper-upper1>1E-10)
{
std::cerr<<upper<<"\t"<<upper1<<std::endl;
fit.set_param_value(pname,upper1);
fit.fit();
Ts s1=fit.get_statistic_value();
fit.set_param_value(pname,upper);
fit.fit();
Ts s=fit.get_statistic_value();
fit.set_param_value(pname,(upper+upper1)/2);
fit.fit();
Ts s01=fit.get_statistic_value();
if((s1-target_chi)*(s01-target_chi)<0&&(s-target_chi)*(s01-target_chi)>=0)
{
upper=(upper+upper1)/2;
}
else if((s1-target_chi)*(s01-target_chi)>0&&(s-target_chi)*(s01-target_chi)<=0)
{
upper1=(upper+upper1)/2;
}
else
{
std::cerr<<"strange statistic structure"<<std::endl;
break;
}
}
for(int i=0;i<fit.get_num_params();++i)
{
fit.set_param_value(pnames[i],pvalues[i]);
}
fit.fit();
////
Tpe lower1=current_value;
step=current_value-lower;
while(1)
{
fit.set_param_value(pname,lower);
fit.fit();
Ts chi=fit.get_statistic_value();
std::cerr<<lower<<"\t"<<chi<<std::endl;
if(chi>current_chi+dchi)
{
break;
}
lower-=step;
}
fit.set_param_value(pname,current_value);
fit.fit();
while(lower1-lower>1E-10)
{
fit.set_param_value(pname,lower1);
fit.fit();
Ts s1=fit.get_statistic_value();
fit.set_param_value(pname,lower);
fit.fit();
Ts s=fit.get_statistic_value();
fit.set_param_value(pname,(lower+lower1)/2);
fit.fit();
Ts s01=fit.get_statistic_value();
//std::cerr<<"l:"<<lower1<<"\t"<<(lower1+lower)/2<<"\t"<<lower<<std::endl;
std::cerr<<s1-target_chi<<"\t"<<s01-target_chi<<"\t"<<s-target_chi<<std::endl;
if((s1-target_chi)*(s01-target_chi)<0&&(s-target_chi)*(s01-target_chi)>=0)
{
lower=(lower+lower1)/2;
}
else if((s1-target_chi)*(s01-target_chi)>0&&(s-target_chi)*(s01-target_chi)<=0)
{
lower1=(lower+lower1)/2;
}
else
{
std::cerr<<"strange statistic structure"<<std::endl;
break;
}
}
dynamic_cast<freeze_param<Ty,Tx,Tp,Tstr>& >(fit.get_param_modifier())-=freeze_param<Ty,Tx,Tp,Tstr>(pname);
for(int i=0;i<fit.get_num_params();++i)
{
fit.set_param_value(pnames[i],pvalues[i]);
}
fit.fit();
}
}
#endif
//EOF
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